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Artificial Intelligence and Decision Making, 2017, Issue 2, Pages 74–77 (Mi iipr246)  

Psycholinguistics

Predictors of aggressiveness indicators

J. M. Kuznetsova

Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow
Abstract: The article presents the results of the analysis of relationships between indicators of aggressiveness determined by a Russian version BPAQ techniques (physical aggression, anger and hostility), on the one hand, and a number of other personality and cognitive characteristics. The sample size was 205 people (average age of 28.4). Using multiple regression method revealed that the propensity to seek social support as coping strategy (Ways of Coping Questionnaire) is a negative predictor of physical aggression (p = 0.05). As predictors of anger are the experience of omnipotence in communication (Personal Myth Questionnaire, p = 0.03) and intolerance to an unsolvable problems (Tolerance to Uncertainty Scale, p = 0,05). Hostility is determined by the search for social support (Ways of Coping Questionnaire, p = 0.01) and a tendency to manipulation in interpersonal relationships (Narcissistic Personality Traits Questionnaire, p = 0.03).
Keywords: aggressiveness, personality traits, cognitive characteristics, regression analysis.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: J. M. Kuznetsova, “Predictors of aggressiveness indicators”, Artificial Intelligence and Decision Making, 2017, no. 2, 74–77
Citation in format AMSBIB
\Bibitem{Kuz17}
\by J.~M.~Kuznetsova
\paper Predictors of aggressiveness indicators
\jour Artificial Intelligence and Decision Making
\yr 2017
\issue 2
\pages 74--77
\mathnet{http://mi.mathnet.ru/iipr246}
\elib{https://elibrary.ru/item.asp?id=29430102}
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  • https://www.mathnet.ru/eng/iipr/y2017/i2/p74
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